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Item Details
| Title:
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FUZZY LOGIC
INTELLIGENCE, CONTROL, AND INFORMATION |
| By: |
John Yen, Reza Langari |
| Format: |
Hardback |
| List price:
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£184.49 |
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We currently do not stock this item, please contact the publisher directly for
further information.
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| ISBN 10: |
0135258170 |
| ISBN 13: |
9780135258170 |
| Publisher: |
PEARSON EDUCATION (US) |
| Pub. date: |
23 November, 1998 |
| Edition: |
United States ed |
| Pages: |
548 |
| Description: |
This text is appropriate for an undergraduate electrical engineering course in fuzzy logic. Providing equal emphasis on theoretical foundations and practical issues, this book features fuzzy logic concepts and techniques in intelligent systems, control, and information technology. |
| Synopsis: |
Providing equal emphasis on theoretical foundations and practical issues, this book features fuzzy logic concepts and techniques in intelligent systems, control, and information technology. FEATURES *Comprehensive and up-to-date coverage. *Provides examples and exercises that are related to real world problems. *Uses Fuzzy Logic Toolbox for MATLABaA A to demonstrate exemplar applications and to develop hands-on exercises. *Provides design guidelines and design methods for developing fuzzy logic applications. *Provides a modern perspective of the fuzzy logic technology. *Introduces core concepts and techniques gently in two steps. *Provides relevant background materials that encompass a wide range of disciplines. *Introduces the connection between fuzzy logic and related ideas, methods, and theories developed in other disciplines (e.g., artificial intelligence, probability theory, control, model identification, etc.). *Summarizes key concepts at the end of each chapter. *Highlights motivations and benefits of employing fuzzy logic in control engineering and information systems. *Discussion of open research issues and their implications.*A chapter is devoted to the subject of "How to design a fuzzy system." In addition, several other chapters (e.g., the chapters on fuzzy model identification and neuro-fuzzy systems) introduce techniques for automating decisions in the design process using training data (i.e., examples) and learning algorithms. *Advanced topics are separated from the basic material in the chapter that immediately follows. |
| Publication: |
US |
| Imprint: |
Prentice Hall |
| Returns: |
Returnable |
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